基于驾驶实践的无人船智能避碰决策方法

Intelligent collision avoidance decision-making method for unmanned ships based on driving practice

[目的]为实现沿海无人驾驶船舶自主航行,充分考虑无人驾驶船舶智能避碰决策的合理性和实时性后,提出并建立一种基于驾驶实践的无人船智能避碰决策方法。[方法]首先,以本体论为基础,设计无人驾驶船舶航行态势本体概念模型,并结合《国际海上避碰规则》及良好的船艺将船舶航行态势量化划分为12种会遇场景;然后,从驾驶实践的角度改进影响碰撞危险度因子的模糊隶属度函数,提出一种多元碰撞危险度评估模型,实现船舶碰撞危险度的精确计算;最后,以船舶避碰总路径最短为目标函数,提出一种基于驾驶员视角(BOP)的智能避碰决策模型,在船舶操纵性、舵角限幅等约束下求解最优避碰策略,并在典型的会遇场景下进行仿真实验。[结果]结果表明,该方法可以准确判断驾驶航行态势,给出合理的转向策略,实现典型会遇场景下的有效避碰。[结论]所做研究可为实现船舶自主航行提供理论基础和方法参考。

[Objective] In order to realize the intelligent navigation and autonomous collision avoidance of unmanned ships in coastal areas, an intelligent collision avoidance decision-making method based on driving practice is proposed. [Method] First, the real-time rationality and uniqueness of the unmanned ship intelligent collision avoidance decision-making process is analyzed. The ontology conceptual model of the navigation situation is then designed and combined with the international regulations for preventing collisions at sea(COLREGS) and good seamanship practices, and the ship encounter scenarios are quantitatively divided into12 types. An improved composite collision risk index assessment model is then proposed from the perspective of piloting practice to reflect collision risk more accurately. Finally, an intelligent collision avoidance decision-making model based on operator’s perspective(BOP) is established, and the optimal collision avoidance strategy is solved by taking the shortest total collision avoidance path as the objective function under the constraints of ship maneuverability and rudder angle amplitude limit. Simulation experiments are then conducted in different obstacle environments. [Results] The simulation results show that this method can accurately determine the piloting situation, provide a reasonable steering strategy and achieve effective collision avoidance in different obstacle environments. [Conclusion] This study provides a theoretical basis and method for realizing the intelligent collision avoidance decision-making and dynamic local collision avoidance path planning of ships.